{"id":"W4405884112","doi":"10.1111/eth.13529","title":"Movement in <scp>3D</scp> : Novel Opportunities for Understanding Animal Behaviour and Space Use","year":2024,"lang":"en","type":"article","venue":"Ethology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ocean Tracking Network; Dalhousie University","funders":"HORIZON EUROPE Framework Programme; Norges Forskningsråd; European Cooperation in Science and Technology; Canada Foundation for Innovation","keywords":"Computer science; Movement (music); Home range; Data science; Ecology; Artificial intelligence; Data mining; Habitat; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003542036,0.0003480389,0.0003322753,0.001133025,0.0004943155,0.002442063,0.0006696028,0.0005338895,0.006890401],"category_scores_gemma":[0.001957583,0.0002068238,0.0006415442,0.001672173,0.001804386,0.00181384,0.001643705,0.0008872878,0.00127804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005315219,"about_ca_system_score_gemma":0.0006093796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01409192,"about_ca_topic_score_gemma":0.01222266,"domain_scores_codex":[0.9997942,0.00005612402,0.00001015455,0.00005780826,0.00006024842,0.00002140508],"domain_scores_gemma":[0.9989954,0.0003647429,0.0001896022,0.0002100507,0.0001624245,0.00007783032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003367783,0.000102377,0.06977603,0.001173927,0.0002971975,0.001431916,0.004342616,0.08654679,0.05022588,0.3742103,0.05608966,0.3554665],"study_design_scores_gemma":[0.00003035838,0.0000998625,0.1862972,0.000409578,0.00007903775,0.001160725,0.00245398,0.3012125,0.005910155,0.347832,0.1542404,0.0002741182],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2502253,0.002554881,0.6513551,0.005962177,0.0005082144,0.0001004106,0.00923082,0.003106097,0.07695704],"genre_scores_gemma":[0.8382882,0.001701272,0.1489775,0.0008344395,0.000255898,0.0001647487,0.002881624,0.0006573134,0.006238906],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01409192,"threshold_uncertainty_score":0.02801979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1435169011537119,"score_gpt":0.2893240258864416,"score_spread":0.1458071247327297,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}